Engineering Feasibility Engineer

BioArk Genome Engineering Operating System (BioArk GEOS) 

Project Vision 

• Current CRISPR software mainly focuses on guide RNA design or individual bioinformatics 

tasks, while successful genome engineering requires engineering strategy selection, feasibility 

analysis, laboratory planning, sequencing validation, quality control, and continuous 

optimization. 

• The BioArk AI CRISPR Engineering Platform is an AI Engineering System implementing a 

Design–Build–Test–Learn (DBTL) workflow. 

• Bioinformatics is treated as one component of a larger engineering ecosystem. 

• The platform leverages biomedical AI systems (e.g. Biomni) for biological reasoning while 

BioArk develops proprietary engineering intelligence, laboratory planning, sequencing 

interpretation and continuous learning.

Engineering Feasibility Analysis Agent Engineers

Role Summary

You will build the AI Engineering Validation Engine, the intelligent "gatekeeper" that verifies whether proposed genome engineering strategies are technically feasible, biologically compatible, and executable using available laboratory resources, vector systems, and manufacturing capabilities.

Key Responsibilities

• Develop AI validation engines to evaluate cloning feasibility, PCR design, construct integrity, and molecular engineering compatibility using bioinformatics and molecular design tools. 
• Design intelligent vector compatibility and delivery validation systems for AAV, Lentivirus, plasmids, PiggyBac, electroporation, and other genome engineering platforms, including cargo size and construct optimization. 
• Build AI resource-matching systems that verify laboratory readiness by assessing reagent availability, instrumentation, personnel, scheduling, and manufacturing capacity. 
• Develop engineering feasibility, technical risk, and manufacturability assessment models that identify potential bottlenecks and recommend alternative implementation strategies before laboratory execution. 

Deliverables

AI Engineering Feasibility Reports, Vector Compatibility & Delivery Analysis Reports, Laboratory Resource Matching Reports, Engineering Risk Assessments, and structured Engineering Validation Packages.

Required Skills

Strong expertise in molecular biology, genome engineering, viral vector systems, cloning technologies, bioinformatics, laboratory automation, Python programming, and AI-driven engineering validation systems.